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A probabilistic approach for solving Poisson equations in computer vision problems

机译:一种求解计算机视觉问题泊松方程的概率方法

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Describes the probabilistic approach to solve Poisson equations and show this method may be used to solve computer vision problems. The authors also give a complexity analysis of this method and compare it method with BEM, FEM and FDM in terms of storage and time complexity. Some examples are given and show that the authors method is better than BEM, FEM and FDM in certain aspects. Finally, the authors use the probabilistic approach for solving several computer vision problems, such as shape from shading, surface interpolation and brightness based stereo vision, the experimental results show that the probabilistic approach is very effective.
机译:描述解决泊松方程的概率方法,并显示该方法可用于解决计算机视觉问题。作者还对该方法进行了复杂性分析,并在存储和时间复杂性方面将其与BEM,FEM和FDM的方法进行比较。给出了一些例子并表明作者方法在某些方面的比例优于BEM,FEM和FDM。最后,作者使用概率方法来解决几种计算机视觉问题,例如遮蔽,表面插值和基于亮度的立体视觉形状,实验结果表明,概率方法非常有效。

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